A model of robust network of networks inspired by brain activities

The human brain is an efficient and robust system composed of multiple interconnected modules which can be described as Network of Networks (NoN). Understanding how the interconnected modules of brain can preserve robustness and functionality is an outstanding problem in many disciplines including Physics, network science, system theory, and neuroscience. Here, we introduce a minimal model of NoN inspired by the pattern of brain activities. We find that the proposed model is robust against typical configuration of external input, rather than catastrophic collapse as in cascading failure model. This model also allows us to identify the core areas in the brain, through the optimization of percolation in the brain networks.